1. FY10 GOES-R3 Project Proposal Title Page

1. 1. FY10 GOES-R3 Project Proposal Title Page • Title: Improved application of GOES water data (vapor and condensed) • Project Type: GOES Utilization • Status: New • Duration: 2 years with potential for FY10 • Leads: • Daniel Birkenheuer ESRL/GSD/Forecast Applications Branch, Federal Service • Other Participants: • Seth Gutman (GPS Expert), Federal Service • Tomoko Koyama (PhD graduate student), CIRES • Yuanfu Xie (DA), Federal Service STMAS (Space Time Multiscale Analysis System) [4Dvar upper level, EnKF surface analysis] • Isidora Jankov (CIRA)

2. 2. Project Summary • Summary • Cal/Val ABI moisture products • A challenge for the GOES-R program since retrievals will be underdetermined and again rely on a model first guess for thermal/moisture profiles – Identify the better model first guess (looking at NAM/RUC) • Take GOES GIMPAP experience with GPSmet Cal/Val and apply it to do ABI moisture data (will show) • Currently assimilating ABI proxy MODIS product data and beginning statistical study • Effort will be to establish dialog with product developers/producers (Jun Li currently), aim to help validate algorithm changes ASAP. Carry tools forward to real GOES R data when it becomes available. • Cloud work • We have experience and good datasets with high temporal cloud/analysis/model data • We are tooling up our modeling and analysis systems to produce synthetic radiances (via CRTM) for cloud work • Plan to steer this into model forecast generated radiances to help in cloud analysis • Expected Result • Cal/Val • Cal/Val tools in place for synthetic ABI moisture product – ready for the “real thing;” can react faster • Error characterization tested and ready to apply to operational product generation and long-term archived data • Develop working relationship with GOES-R applications development and other cal/Val working groups • Cloud work • Operate radiance forecasts (with CRTM) of clear then cloudy scenes • Test against observations • Enhanced techniques to assess cloud phase and layer fraction within a single pixel • Encourage collaboration with AOML

3. 3. Motivation/Justification • Supports NOAA Mission Goal(s): • Weather and Water • Climate (climate record) • Motivation • GOES-R AWG team has identified 2 main areas of focus included here • Calibration and Validation • We view the inclusion of GPSmet technology (ground based real time total precipitable water) as an essential part of a sustained calibration support ingredient as recommended by the AWG Application Team. • As recommended by the team, we are already using MODIS as a model for this activity. • GPSmet is a state-of-the-art technology proven ready for cal/val. • Climate Record (GOES will be part of any high temporal climate record) – quality • Clouds • The AWG Team emphasizes multi-layer cloud assessment/analysis using remote sensing. Explore using our cloud analysis with addition of GOES radiances from CRTM • We are currently looking at interfacing our GOES assimilation schemes in real time using CSU GOES R cloud and other products (early 09) • This year the effort focused on our spin-up of CRTM utilities. Will enable cloud fraction and optical properties to be included in our analysis.

4. 4. Methodology • Continuity with current effort • GOES error studies for calibration and validation • Examine current candidates for first guess moisture fields and assess/recommend using GPS. • Look at specific features of time series of GOES east corrections with GPS to infer possibly more information [solar/emissivity issues?] • Expand the dialog and collaboration with NESDIS and CIMSS • Sustain a long-term statistical comparison data set with GPS and proxy GOES R (MODIS) and subsequent transition to GOES R [underway] • Further work with cloud analysis and Cloud Sat data utilizing GOES information. • When available obtain GOES R simulated model data from CSU and examine cloud analysis methodology (early 10) • We have a CRTM interface created that will enable interface to our local analysis/modeling system to better exploit and detect issues in GOES assimilation/CRTM application. Looking to establish integration into STMAS, HFIP, and AOML ties • Long term interest in developing a variational CRTM based, GOES /GOES R refinement to our existing cloud analysis for different cloud emissivity values.

5. 5. Summary of Previous Results • Calibration and Validation (AWG) FY09 to date • Still see moist bias in the operational product. CIMSS new product still looking good. (Gutman) • Both background model (GFS) and GOES 12 operational product becoming more moist with time. • Recommend switch to CIMSS algorithm or bias correction. • Think about better first guess at least for CONUS products. • Cloud Work (GOES-R) • CRTM now working on multiple platforms, producing simulated radiances. (ECMWF test profiles, and WRF model forecasts) • CRTM testing surface conditions and simulated radiance, solar influence in the near IR, cloud microphysics from modeled condensate. • Working on meshing the CRTM with 4Dvar STMAS system.

6. Operational GOES W Operational GOES E Current statistics from ~1 year to present

7. ABI (MODIS simulation) – note good bias but large RMS

8. Test CIMSS product GOES E same time Operational GOES E (shown earlier) Current statistics for ~1 year to present

9. Observed visible image ~6/13/02 00h WRF model run (24h) valid 3/13/02 00h (WV)

10. Observed IR window ~6/13/02 00h WRF modeled IR radiances (24h run) Valid 6/13/02 00h

11. HFIP GFS model run for hurricane Katrina case. Radiances generated from CRTM for window IR channel. 06h forecast

12. 6. Expected Outcomes • Calibration and Validation (AWG) • GPS (independent) asynoptic validation of new algorithms. • Moisture profile error reduction that would thereby serve to improve thermal retrievals and serve to optimize ABI first guess • Clouds (GOES-R) • Better characterize clouds in the analysis system that uses GOES cloud data for a large part of its operation. (STMAS) • Improve cloud representation in model output (radiance representation) • Assess impact on model initialization through hot-start techniques (driven largely by ABI cloud radiances and products) • Ultimate goal is assimilation of cloudy pixels using adjoint system with STMAS and better forecast with WRF. • Collaboration between GSD and Louie Grasso (CIRA)

13. 7. Major Milestones • FY09 • Kept project running through period with no funding. (AWG) • On track with CRTM and cloudy pixel work • FY10 • Off shore GPS, comparison of IR and MW b-temps over open ocean (<40km offshore). Quantify relative and absolute differences – better boundary conditions for model. (AWG) • Incorporate CRTM adjoint in STMAS (GOES R) • Improve simulation of cloudy radiances in the WRF model with CRTM. (GOES R) • Push for a visible channel output in CRTM. (GOES R) • Match model resolution with satellite pixel resolution to assimilate pixels (or as close to possible) (GOES R) • Validate forecasts (GOES R) • Examine microphysical effects (GSD – CIRA collaboration)

14. 8. Funding Profile (K)* • Summary of leveraged funding • GPS-met – offers data from existing and new platforms for AWG efforts (offshore platforms in the Gulf). • HFIP (hurricane forecast intensity prediction) – covers some costs of CRTM integration effort. • HMT – WRF utilization of CRTM, more GPS sites in SE for program starting FY10 • OSSE – utilizes WRF radiances, covers some costs of CRTM implementation * Funding figures are money received by ESRL after any NESDIS taxing, also includes the funding of Federal workers (see breakout next slide)

15. 9. Expected Purchase Items • FY09 • AWG (component): 37.5K • 13.2k Salaries 2 people at 315hrs (total) time from Mar 08 to Sept 09 • 9.4k Personnel overhead • 14.3k Facilities • 0.6k Travel • GOESR3 (component): 87.5K • 30.7k Salaries 3 people at 735hrs (total) time from Mar 08 to Sept 09 • 21.9k Personnel overhead • 33.5k Facilities • 1.4k Travel • FY10 • AWG: 87.5k • 27.5k Salaries all Federal (440 hr) • 25.6k Personnel overhead • 33.4k Facilities (sys ads, network, data warehouse, servers – for this project) • 1k Travel • GOES R3: 122.4k • 33.9k Salaries (CIRA, CIRES) (1280 hr) • 14.2k Salaries Federal (224hr) • 14.1k Personnel overhead CIRA,CIRES • 13.2k Personnel overhead Federal • 44.0k Facilities (sys ads, network, data warehouse, servers – for this project) • 3k Travel